Dataset for Quantum Circuits Mapping

The proposed dataset helps to address the quantum circuit mapping problem as a classification task. Three csv files are provided, each one refers to a specific IBM quantum machine, namely IBMQ Santiago, IBMQ Athens, and IBMQ 16 Melbourne. Each csv file is composed of random quantum circuits mapped onto the specific IBM quantum processor. In detail, each dataset instance contains some features related to the calibration data of the physical device and others related to the generated quantum circuit. Finally, the instance is labeled with a vector encoding the best mapping among those provided by deterministic mapping algorithms.

本研究提出的数据集可将量子电路映射（quantum circuit mapping）问题建模为分类任务，助力该问题的解决。本次共提供三个CSV文件，每个文件对应一款特定的IBM量子计算机，分别为IBMQ Santiago、IBMQ Athens及IBMQ 16 Melbourne。各CSV文件均包含映射至对应IBM量子处理器的随机量子电路相关数据。具体而言，每个数据集实例包含两类特征：一类与物理设备的校准数据相关，另一类与生成的量子电路相关。最终，每个实例将通过一个向量进行标注，该向量编码了确定性映射算法所提供的候选映射方案中的最优映射。